Identification model of the independence right-fuzzy variable theory of water inrush source

Authors

DONG Donglin, College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China; National Engineering Research Center of Coal Mine Water Hazard Controlling, Beijing 100083, China
LI Xiang, College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China; National Engineering Research Center of Coal Mine Water Hazard Controlling, Beijing 100083, China
LIN Gang, College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China; National Engineering Research Center of Coal Mine Water Hazard Controlling, Beijing 100083, ChinaFollow
BIAN Jianling, Beijing China-Power Information Technology Co. Ltd., Beijing 100085, China
CAO Chenglong, College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China; National Engineering Research Center of Coal Mine Water Hazard Controlling, Beijing 100083, China
WU Heng, College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China; National Engineering Research Center of Coal Mine Water Hazard Controlling, Beijing 100083, China

Abstract

In the process of coal mining, mine water hazard accidents occur frequently. In order to find out the water source of mine water inrush quickly and accurately, and reduce the harm caused by mine water inrush to coal mine production, taking Zhaogezhuang mine as an example, and the method of combining independent weight coefficient with fuzzy variable theory was used to select six kinds of hydrochemical indexes of Na⁺, Ca²⁺, Mg²⁺, Cl^-, SO₄^2- and HCO₃^-, 20 sets of water sample data of Zhaogezhuang mine were analyzed and calculated. The results showed that independence weight coefficient-fuzzy variable model eliminated the influence of redundant information among indexes in water samples, overcame the difficulty of determining the weight among variables in water samples and the uneven influence of variables on water quality, and ensured the accuracy of water inrush source identification model to a certain extent. The weight of Cl^- was much larger than that of other chemical indexes, that means, Cl^- had a great influence on the identification results of water inrush sources. This paper established a model to discriminate eight groups of water samples in Zhaogezhuang mine, the accuracy of the identification was 87.5%. It shows that the model has certain application value in identifying the source of mine water inrush.

Keywords

identification of water inrush source, independent weight coefficient method, fuzzy variable set theory, chemical index, Zhaogezhuang mine

DOI

10.3969/j.issn.1001-1986.2019.05.007

Recommended Citation

DONG Donglin, LI Xiang, LIN Gang, et al. (2019) "Identification model of the independence right-fuzzy variable theory of water inrush source," Coal Geology & Exploration: Vol. 47: Iss. 5, Article 8.
DOI: 10.3969/j.issn.1001-1986.2019.05.007
Available at: https://cge.researchcommons.org/journal/vol47/iss5/8

Reference

[1] 武强,崔芳鹏,赵苏启,等. 矿井水害类型划分及主要特征分析[J]. 煤炭学报,2013,38(4):561-565. WU Qiang,CUI Fangpeng,ZHAO Suqi,et al. Type classification and main characteristics of mine water disasters[J]. Journal of China Coal Society,2013,38(4):561-565.

[2] 董东林,孙录科,马靖华,等. 郑州矿区突水模式及防治对策研究[J]. 采矿与安全工程学报,2010,27(3):363-369. DONG Donglin,SUN Luke,MA Jinghua,et al. Water inrush mode and countermeasures for Zhengzhou mining area[J]. Journal of Mining & Safety Engineering,2010,27(3):363-369.

[3] 王心义,徐涛,黄丹. 距离判别法在相似矿区突水水源识别中的应用[J]. 煤炭学报,2011,36(8):1354-1358. WANG Xinyi,XU Tao,HUANG Dan. Application of distance discriminance in identifying water inrush resource in similar coalmine[J]. Journal of China Coal Society,2011,36(8):1354-1358.

[4] 张好,姚多喜,鲁海峰,等. 主成分分析与Bayes判别法在突水水源判别中的应用[J]. 煤田地质与勘探,2017,45(5):87-93. ZHANG Hao,YAO Duoxi,LU Haifeng,et al. Application of principal component analysis and Bayes discrimination approach in water source identification[J]. Coal Geology & Exploration,2017,45(5):87-93.

[5] 张春雷,钱家忠,赵卫东,等. Bayes方法在矿井突水水源判别中的应用[J]. 煤田地质与勘探,2010,38(4):34-37. ZHANG Chunlei,QIAN Jiazhong,ZHAO Weidong,et al. The application of Bayesian approach to discrimination of mine water-inrush source[J]. Coal Geology & Exploration,2010,38(4):34-37.

[6] WU Qiang,FAN Shukai,ZHOU Wanfang,et al. Application of the analytic hierarchy process to assessment of water inrush:A case study for the No.17 coal seam in the Sanhejian coal mine China[J]. Mine Water and the Environment,2013,32(3):229-238.

[7] 陈红江,李夕兵,刘爱华,等. 用Fisher判别法确定矿井突水水源[J]. 中南大学学报(自然科学版),2009,40(4):1114-1120. CHEN Hongjiang,LI Xibing,LIU Aihua,et al. Identifying of mine water inrush sources by Fisher discriminant analysis method[J]. Journal of Central South University(Science and Technology),2009,40(4):1114-1120.

[8] 王震,朱术云,段宏飞,等. 基于灰色系统关联分析的矿井突水水源判别[J]. 煤矿安全,2012,43(7):132-135. WANG Zhen,ZHU Shuyun,DUAN Hongfei,et al. Discrimination of water-bursting source based on grey correlative analysis[J]. Safety in Coal Mines,2012,43(7):132-135.

[9] 高卫东. 熵权模糊综合评价法在矿井突水水源判别中的应用[J]. 矿业安全与环保,2012,39(2):22-24. GAO Weidong. Application of fuzzy comprehensive evalua-tion method of entropy weight in the identification of mine water inrush source[J]. Mining Safety & Environmental Protection,2012,39(2):22-24.

[10] WU Jiansong,XU Shengdi,ZHOU Rui,et al. Scenario analysis of mine water inrush hazard using Bayesian networks[J]. Safety Science,2016,89:231-239.

[11] 王志杰,李昭,马德林,等. 基于灰色理论的雪山梁隧道施工过程渗漏水水源识别研究[J]. 隧道建设,2017,37(1):24-29. WANG Zhijie,LI Zhao,MA Delin,et al. Research on water source identification of water leakage during construction of Xueshanliang tunnel based on grey theory[J]. Tunnel Construction,2017,37(1):24-29.

[12] 李兴华,杨勇. 基于PCA-Bayes的矿井水源类型在线判别模型[J]. 煤炭与化工,2018,41(2):21-25. LI Xinghua,YANG Yong. Online discrimination system for mine water inrush source based on PCA-Bayes[J]. Coal and Chemical Industry,2018,41(2):21-25.

[13] 张妹,刘启蒙,张宇通. 基于PCA分析的突水水源Fisher判别模型[J]. 煤炭技术,2018,37(3):172-174. ZAHNG Mei,LIU Qimeng,ZHANG Yutong. Fisher discrimination model for sources of mine water inrush based on PCA analysis[J]. Coal Technology,2018,37(3):172-174.

[14] 杨海军,王广才. 煤矿突水水源判别与水量预测方法综述[J]. 煤田地质与勘探,2012,40(3):48-54. YANG Haijun,WANG Guangcai. Summarization of methods of distinguishing sources and forecasting inflow of water inrush in coal mines[J]. Coal Geology & Exploration,2012,40(3):48-54.

[15] 张淑莹,胡友彪,邢世平,等. 基于独立性权-灰色关联度理论的突水水源判别[J]. 水文地质工程地质,2018,45(6):36-41. ZHANG Shuying,HU Youbiao,XING Shiping,et al. Discrimination of the mine water inrush source based on principal component analyses-theory of gray relational degree[J]. Hydrogeology & Engineering Geology,2018,45(6):36-41.

[16] 陈善雄,刘小娟,陈春蓉,等. 针对Lasso问题的多维权重求解算法[J]. 计算机应用,2017,37(6):1674-1679. CHEN Shanxiong,LIU Xiaojuan,CHEN Chunrong,et al. Method for solving Lasso problem by utilizing multi-dimensional weight[J]. Journal of Computer Applica-tions,2017,37(6):1674-1679.

[17] 陈守煜,韩晓军. 围岩稳定性评价的模糊可变集合工程方法[J]. 岩石力学与工程学报,2006,25(9):1857-1861. CHEN Shouyu,HAN Xiaojun. Engineering method of variable fuzzy set for assessment of surrounding rock stability[J]. Chinese Journal of Rock Mechanics and Engineering,2006,25(9):1857-1861.

[18] WANG Yuankun,SHENG Dong,WANG Dong,et al. Variable fuzzy set theory to assess water quality of the Meiliang bay in Taihu lake basin[J]. Water Resources Management,2014,28(3):867-880.

[19] 王心义,赵伟,刘小满,等. 基于熵权-模糊可变集理论的煤矿井突水水源识别[J]. 煤炭学报,2017,42(9):2433-2439. WANG Xinyi,ZHAO Wei,LIU Xiaoman,et al. Identification of water inrush source from coalfield based on entropy weight-fuzzy variable set theory[J]. Journal of China Coal Society,2017,42(9):2433-2439.

[20] 陈建生,何会祥,王涛. 基于熵权-可变模糊集模型的堤坝渗漏探测[J]. 河海大学学报(自然科学版),2016,44(4):358-363. CHEN Jiansheng,HE Huixiang,WANG Tao. Dam leakage detection based on entropy weight-variable fuzzy set model[J]. Journal of Hohai University(Natural Sciences),2016,44(4):358-363.

[21] 邱林,王文川,陈守煜. 农业旱灾脆弱性定量评估的可变模糊分析法[J]. 农业工程学报,2011,27(增刊2):61-65. QIU Lin,WANG Wenchuan,CHEN Shouyu. Quantitative estimation for vulnerability of agricultural drought disaster using variable fuzzy analysis method[J]. Transactions of the Chinese Society of Agricultural Engineering,2011,27(S2):61-65.